When Machine Learning technologies are used in contexts that affect citizens, companies as
well as researchers need to be confident that there will not be any unexpected social …

Artificial Intelligence (AI)‐based systems are widely employed nowadays to make decisions
that have far‐reaching impact on individuals and society. Their decisions might affect …

In the past few decades, artificial intelligence (AI) technology has experienced swift
developments, changing everyone's daily life and profoundly altering the course of human …

As machine learning increasingly affects people and society, it is important that we strive for
a comprehensive and unified understanding of how and why unwanted consequences …

We present a large-scale study of gender bias in occupation classification, a task where the
use of machine learning may lead to negative outcomes on peoples' lives. We analyze the …

Operating at a large scale and impacting large groups of people, automated systems can
make consequential and sometimes contestable decisions. Automated decisions can impact …

Non-discrimination is a recognized objective in algorithmic decision making. In this paper,
we introduce a novel probabilistic formulation of data pre-processing for reducing …

The combination of increased availability of large amounts of fine-grained human behavioral
data and advances in machine learning is presiding over a growing reliance on algorithms …

Ensuring fairness of machine learning systems is a human-in-the-loop process. It relies on
developers, users, and the general public to identify fairness problems and make …

Recent work has raised concerns on the risk of unintended bias in AI systems being used
nowadays that can affect individuals unfairly based on race, gender or religion, among other …